1. Tutorial 5: Discrete Probability I Reference:http://www.cs.duke.edu/courses/fall07/ cps102/lecture11.ppt Steve Gu Feb 15, 2008

2. Language of Probability The formal language of probability is a very important tool in describing and analyzing probability distribution

3. Probability Space A Probability space has 3 elements: – Sample Space : Ω All the possible individual outcomes of an experiment – Event Space : ₣ Set of all possible subsets of elements taken from Ω – Probability Measure : P A mapping from event space to real numbers such that for any E and F from ₣ – P(E)>=0 – P(Ω)=1 – P(E union F) = P(E) + P(F) We can write a probability space as (Ω, ₣,P)

4. Ω Sample space Sample Space: Ω p(x) = 0.2 probability of x 0.2 0.13 0.06 0.11 0.17 0.1 0.13 0 0.1

5. Events Any set E  Ω is called an event  p(x) x  E Pr D [E] = S 0.17 0.1 0.13 0 Pr D [E] = 0.4

6. Uniform Distribution If each element has equal probability, the distribution is said to be uniform  p(x) = x  E Pr D [E] = |E| |Ω||Ω|

7. A fair coin is tossed 100 times in a row What is the probability that we get exactly half heads?

8. The sample space Ω is the set of all outcomes {H,T} 100 Each sequence in Ω is equally likely, and hence has probability 1/|Ω|=1/2 100 Using the Language

9. Ω = all sequences of 100 tosses x = HHTTT……TH p(x) = 1/|Ω| Visually

10. Set of all 2 100 sequences {H,T} 100 Probability of event E = proportion of E in Ω Event E = Set of sequences with 50 H’s and 50 T’s 100 50 / 2 100

11. Suppose we roll a white die and a black die What is the probability that sum is 7 or 11?

12. (1,1), (1,2), (1,3), (1,4), (1,5), (1,6), (2,1), (2,2), (2,3), (2,4), (2,5), (2,6), (3,1), (3,2), (3,3), (3,4), (3,5), (3,6), (4,1), (4,2), (4,3), (4,4), (4,5), (4,6), (5,1), (5,2), (5,3), (5,4), (5,5), (5,6), (6,1), (6,2), (6,3), (6,4), (6,5), (6,6) } Pr[E] = |E|/|Ω| = proportion of E in S = 8/36 Same Methodology! Ω = {

13. 23 people are in a room Suppose that all possible birthdays are equally likely What is the probability that two people will have the same birthday?

14. x = (17,42,363,1,…, 224,177) 23 numbers And The Same Methods Again! Sample space Ω = {1, 2, 3, …, 366} 23 Event E = { x  W | two numbers in x are same } Count |E| instead!What is |E|?

15. all sequences in S that have no repeated numbers E = |Ω| = 366 23 |E| = (366)(365)…(344) = 0.494… |Ω||Ω| |E| |Ω||Ω| = 0.506…

16. and is defined to be = S A B proportion of A  B More Language Of Probability The probability of event A given event B is written Pr[ A | B ] to B Pr [ A  B ] Pr [ B ]

17. event A = {white die = 1} event B = {total = 7} Suppose we roll a white die and black die What is the probability that the white is 1 given that the total is 7?

18. (1,1), (1,2), (1,3), (1,4), (1,5), (1,6), (2,1), (2,2), (2,3), (2,4), (2,5), (2,6), (3,1), (3,2), (3,3), (3,4), (3,5), (3,6), (4,1), (4,2), (4,3), (4,4), (4,5), (4,6), (5,1), (5,2), (5,3), (5,4), (5,5), (5,6), (6,1), (6,2), (6,3), (6,4), (6,5), (6,6) } Ω = { |B| Pr[B] 1/6 |A  B| =Pr [ A | B ] Pr [ A  B ] 1/36 == event A = {white die = 1}event B = {total = 7}

19. Independence! A and B are independent events if Pr[ A | B ] = Pr[ A ]  Pr[ A  B ] = Pr[ A ] Pr[ B ]  Pr[ B | A ] = Pr[ B ]

20. E.g., {A 1, A 2, A 3 } are independent events if: Pr[A 1 | A 2  A 3 ] = Pr[A 1 ] Pr[A 2 | A 1  A 3 ] = Pr[A 2 ] Pr[A 3 | A 1  A 2 ] = Pr[A 3 ] Pr[A 1 | A 2 ] = Pr[A 1 ]Pr[A 1 | A 3 ] = Pr[A 1 ] Pr[A 2 | A 1 ] = Pr[A 2 ] Pr[A 2 | A 3 ] = Pr[A 2 ] Pr[A 3 | A 1 ] = Pr[A 3 ]Pr[A 3 | A 2 ] = Pr[A 3 ] Independence! A 1, A 2, …, A k are independent events if knowing if some of them occurred does not change the probability of any of the others occurring

21. Silver and Gold One bag has two silver coins, another has two gold coins, and the third has one of each One bag is selected at random. One coin from it is selected at random. It turns out to be gold What is the probability that the other coin is gold?

22. Let G 1 be the event that the first coin is gold Pr[G 1 ] = 1/2 Let G 2 be the event that the second coin is gold Pr[G 2 | G 1 ] = Pr[G 1 and G 2 ] / Pr[G 1 ] = (1/3) / (1/2) = 2/3 Note: G 1 and G 2 are not independent

23. The Monty Hall Problem http://www.youtube.com/watch?v=mhlc7peGlGg

24. The Monty Hall Problem http://en.wikipedia.org/wiki/Monty_Hall_problem

25. The Monty Hall Problem

26. Still doubt? Try playing the game online: – http://www.theproblemsite.com/games/mo nty_hall_game.asp http://www.theproblemsite.com/games/mo nty_hall_game.asp

27. Thank you! Q&A